Topics in Applied Analysis and Optimisation: Partial Differential Equations, Stochastic and Numerical Analysis, Hintermьller Michael, Rodrigues Josй Francisco

Автор: Oksendal
Название: Stochastic Differential Equations
ISBN: 3540047581 ISBN-13(EAN): 9783540047582
Издательство: Springer
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Цена: 54820.00 T
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Описание: Gives an introduction to the basic theory of stochastic calculus and its applications. This book offers examples in order to motivate and illustrate the theory and show its importance for many applications in for example economics, biology and physics.

Автор: Deo Naokant, Gupta Vijay, Acu Ana Maria
Название: Mathematical Analysis II: Optimisation, Differential Equations and Graph Theory: Icrapam 2018, New Delhi, India, October 23-25
ISBN: 981151156X ISBN-13(EAN): 9789811511561
Издательство: Springer
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Цена: 93160.00 T
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Описание: This book collects original research papers and survey articles presented at the International Conference on Recent Advances in Pure and Applied Mathematics (ICRAPAM), held at Delhi Technological University, India, on 23-25 October 2018.

Автор: Michael Hinterm?ller; Jos? Francisco Rodrigues
Название: Topics in Applied Analysis and Optimisation
ISBN: 3030331156 ISBN-13(EAN): 9783030331153
Издательство: Springer
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Цена: 139750.00 T
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Описание: This volume comprises selected, revised papers from the Joint CIM-WIAS Workshop, TAAO 2017, held in Lisbon, Portugal, in December 2017. The workshop brought together experts from research groups at the Weierstrass Institute in Berlin and mathematics centres in Portugal to present and discuss current scientific topics and to promote existing and future collaborations. The papers include the following topics: PDEs with applications to material sciences, thermodynamics and laser dynamics, scientific computing, nonlinear optimization and stochastic analysis.

Автор: Kontoghiorghes Erricos J., Gatu Cristian
Название: Optimisation, Econometric and Financial Analysis
ISBN: 3540366253 ISBN-13(EAN): 9783540366256
Издательство: Springer
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Цена: 153720.00 T
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Описание: Advanced computational methods are often employed for the solution of modelling and decision-making problems. This book addresses issues associated with the interface of computing, optimisation, econometrics and financial modelling. Emphasis is given to computational optimisation methods and techniques. The first part of the book addresses optimisation problems and decision modelling, with special attention to applications of supply chain and worst-case modelling as well as advances in the methodological aspects of optimisation techniques. The second part of the book is devoted to optimisation heuristics, filtering, signal extraction and various time series models. The chapters in this part cover the application of threshold accepting in econometrics, the structure of threshold autoregressive moving average models, wavelet analysis and signal extraction techniques in time series. The third and final part of the book is about the use of optimisation in portfolio selection and real option modelling.

Автор: Erricos Kontoghiorghes; Cristian Gatu
Название: Optimisation, Econometric and Financial Analysis
ISBN: 3642071716 ISBN-13(EAN): 9783642071713
Издательство: Springer
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Цена: 153720.00 T
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Описание: This book addresses issues associated with the interface of computing, optimisation, econometrics and financial modeling, emphasizing computational optimisation methods and techniques.

Автор: Marquez Calvo, Oscar Osvaldo
Название: Advancing Robust Multi-Objective Optimisation Applied to Complex Model-Based Water-Related Problems
ISBN: 0367460432 ISBN-13(EAN): 9780367460433
Издательство: Taylor&Francis
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Цена: 74510.00 T
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Описание: A framework for robust optimisation of multiple objectives and multiple sources of uncertainty is proposed, which integrates widely accepted robustness metrics, is tested in engineering problems related to the water sector, in particular the design of urban drainage and water distribution systems.

Автор: Desmond J. Higham, Peter E. Kloeden
Название: An Introduction to the Numerical Simulation of Stochastic Differential Equations
ISBN: 1611976421 ISBN-13(EAN): 9781611976427
Издательство: Mare Nostrum (Eurospan)
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Цена: 66050.00 T
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Описание: This book provides a lively and accessible introduction to the numerical solution of stochastic differential equations with the aim of making this subject available to the widest possible readership. It presents an outline of the underlying convergence and stability theory while avoiding technical details. Key ideas are illustrated with numerous computational examples and computer code is listed at the end of each chapter. The authors include 150 exercises, with solutions available online, and 40 programming tasks.Although introductory, the book covers a range of modern research topics, including It? versus Stratonovich calculus, implicit methods, stability theory, nonconvergence on nonlinear problems, multilevel Monte Carlo, approximation of double stochastic integrals, and tau leaping for chemical and biochemical reaction networks.An Introduction to the Numerical Simulation of Stochastic Differential Equations is appropriate for undergraduates and postgraduates in mathematics, engineering, physics, chemistry, finance, and related disciplines, as well as researchers in these areas. The material assumes only a competence in algebra and calculus at the level reached by a typical first-year undergraduate mathematics class, and prerequisites are kept to a minimum. Some familiarity with basic concepts from numerical analysis and probability is also desirable but not necessary.

Автор: Bao Gang, Coron Jean-Michel, Li Ta-Tsien
Название: Control and Inverse Problems for Partial Differential Equations
ISBN: 9813276142 ISBN-13(EAN): 9789813276147
Издательство: World Scientific Publishing
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Цена: 105600.00 T
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Описание: This book is a collection of lecture notes for the LIASFMA Hangzhou Autumn School on 'Control and Inverse Problems for Partial Differential Equations' which was held during October 17-22, 2016 at Zhejiang University, Hangzhou, China. This autumn school is one of the activities organized by Sino-French International Associate Laboratory in Applied Mathematics (LIASFMA). Established jointly by eight institutions in China and France in 2014, LIASFMA aims at providing a platform for many leading French and Chinese mathematicians to conduct in-depth researches, extensive exchanges, and student training in broad areas of applied mathematics.The book provides the readers with a unique and valuable opportunity to learn from and communicate with leading experts in control and inverse problems. And the readers are exposed not only to the basic theories and methods but also to the forefront of research directions in both fields.

Автор: Coron Jean-Michel, Li Ta-Tsien, Li Yachun
Название: One-Dimensional Hyperbolic Conservation Laws and Their Applications
ISBN: 9813276177 ISBN-13(EAN): 9789813276178
Издательство: World Scientific Publishing
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Цена: 137280.00 T
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Описание: This book is a collection of lecture notes for the LIASFMA Shanghai Summer School on 'One-dimensional Hyperbolic Conservation Laws and Their Applications' which was held during August 16 to August 27, 2015 at Shanghai Jiao Tong University, Shanghai, China. This summer school is one of the activities promoted by Sino-French International Associate Laboratory in Applied Mathematics (LIASFMA in short). LIASFMA was established jointly by eight institutions in China and France in 2014, which is aimed at providing a platform for some of the leading French and Chinese mathematicians to conduct in-depth researches, extensive exchanges, and student training in the field of applied mathematics. This summer school has the privilege of being the first summer school of the newly established LIASFMA, which makes it significant.

Автор: Lord
Название: An Introduction to Computational Stochastic PDEs
ISBN: 0521899907 ISBN-13(EAN): 9780521899901
Издательство: Cambridge Academ
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Цена: 121440.00 T
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Описание: This comprehensive introduction to stochastic partial differential equations incorporates the effects of randomness into real-world models, offering graduate students and researchers powerful tools for understanding uncertainty quantification for risk analysis. MATLAB (R) codes are included, so that readers can perform computations themselves and solve the test problems discussed.

Автор: Martin J. Gander, Felix Kwok
Название: Numerical Analysis of Partial Differential Equations Using Maple and MATLAB
ISBN: 1611975301 ISBN-13(EAN): 9781611975307
Издательство: Mare Nostrum (Eurospan)
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Цена: 56850.00 T
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Описание: This book provides an elementary yet comprehensive introduction to the numerical solution of partial differential equations (PDEs). Used to model important phenomena, such as the heating of apartments and the behavior of electromagnetic waves, these equations have applications in engineering and the life sciences, and most can only be solved approximately using computers.Numerical Analysis of Partial Differential Equations Using Maple and MATLAB provides detailed descriptions of the four major classes of discretization methods for PDEs (finite difference method, finite volume method, spectral method, and finite element method) and runnable MATLAB® code for each of the discretization methods and exercises. It also gives self-contained convergence proofs for each method using the tools and techniques required for the general convergence analysis but adapted to the simplest setting to keep the presentation clear and complete.This book is intended for advanced undergraduate and early graduate students in numerical analysis and scientific computing and researchers in related fields. It is appropriate for a course on numerical methods for partial differential equations.

Автор: Lord
Название: An Introduction to Computational Stochastic PDEs
ISBN: 0521728525 ISBN-13(EAN): 9780521728522
Издательство: Cambridge Academ
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Цена: 60190.00 T
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Описание: This comprehensive introduction to stochastic partial differential equations incorporates the effects of randomness into real-world models, offering graduate students and researchers powerful tools for understanding uncertainty quantification for risk analysis. MATLAB (R) codes are included, so that readers can perform computations themselves and solve the test problems discussed.